Production Process Protocols for Multi-Station Object Tracking
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Solution Overview
Problem
Current methods fail to provide detailed monitoring and analysis of manufacturing or processing steps for products across multiple stations, leading to delays and inefficiencies in production processes, as they only track product location and not specific processing steps or machine performance.
Innovation Solution
A method involving machine-readable data assigned to objects, read by sensors at each production station, generating process protocols with timestamps and context-related data, which are stored and analyzed to visualize and monitor the entire production process, including machine and sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If only barcode reading means are provided at predetermined locations to track product location, then the system can answer which product is currently located at which point, but it cannot determine which manufacturing or processing step has been taken for which product
Solution Approach 1:
The monitoring system is segmented into multiple reading means distributed at different production stations, each capturing data at specific locations. This segmentation allows the system to collect processing step information without requiring a single complex centralized monitoring device
Solution Approach 2:
A data processing unit acts as an intermediary that receives data from multiple reading means and generates process protocols. This intermediary component synthesizes information from various stations to provide comprehensive processing step tracking without requiring direct complex interaction between all system components
2Measurement precision
If reading means are provided at each production station to read machine-readable data, then detailed processing information can be collected, but the system complexity and data processing requirements increase
Solution Approach 1:
The reading means are designed with multi-functionality, capable of reading various types of machine-readable data (barcodes, RFID tags, data matrices) at different production stations. This universal design reduces the need for station-specific reading devices, thereby reducing overall system complexity while maintaining high measurement precision
Solution Approach 2:
Instead of physically tracking each product through complex sensor arrays, the system uses copies of product information encoded in machine-readable data. These data copies are read at each station and processed to reconstruct the complete processing history, reducing physical monitoring complexity while maintaining detailed tracking precision
3Productivity
If process protocols are generated from machine-readable data with timestamps and context-related data, then bottlenecks and errors can be identified, but the data processing and storage requirements increase
Solution Approach 1:
The data processing unit extracts only the essential information needed for process protocol generation from the raw machine-readable data and sensor readings. By taking out only the critical data elements (product ID, timestamp, station ID, process step), the system reduces data volume while maintaining the capability to identify bottlenecks and errors
Solution Approach 2:
Context-related data is collected and pre-processed at each production station before being transmitted to the central processing unit. This preliminary action at the source reduces the data volume that needs to be transmitted and processed centrally, thereby reducing overall data storage requirements while enabling efficient bottleneck identification
Data Source
AI summary
A method of providing process protocols for physical objects, which pass through several production/processing stations in a production/processing line, is provided. In such a method, machine-readable data for uniquely identifying an object are assigned to the object, a reading means is arranged at a production/processing station, by which machine-readable data can be read, a time stamp is assigned to the data, and a process protocol is generated from the machine-readable data, an assignment of the data to the station and/or to the reading means and the time stamp. Each data set describes a process step of a process, and comprises at least a first attribute, in which a unique identification of a process is stored, a second attribute, in which an identification of the process step is stored, and a third attribute, in which a sequence of the process steps within a process is stored.